Data Science Certification Course - Python

Edureka’s Data Science Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. This Data Science Certification Training exposes you to concepts of Statistics, Time Series and different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. Throughout the Data Science Certification Course you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR.

Cloud Lab New

Edureka’s Python Data Science course is
designed to make you grab the concepts of Machine Learning. The course will
provide deep understanding of Machine Learning and its mechanism. As a Data
Scientist, you will be learning the importance of Machine Learning and its
implementation in python programming language. Furthermore, you will be taught
of Reinforcement Learning which in turn is an important aspect of Artificial
Intelligence. You will be able to automate real life scenarios using Machine
Learning Algorithms. Towards the end of the course we will be discussing
various practical use cases of Machine Learning in python programming language
to enhance your learning experience.

Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.

The pre-requisites for the Data Science with Python Course includes development experience with Python. Fundamentals of Data Analysis practiced over any of the data analysis tools like SAS/R will be a plus. However, Python would be more advantageous. You will be provided with complementary “Statistics Essentials for Analytics” as a self-paced course once you enroll for the course.

You don’t have to worry about the System Requirements as you will be doing your Practical on a Cloud LAB environment. This environment already contains all the necessary software that will be required to execute your practicals.

You will do your Assignments/Case Studies using Jupyter Notebook that is already installed on your Cloud LAB environment whose access details will be available on your LMS. You will be accessing your Cloud LAB environment from a browser. For any doubt, the 24*7 support team will promptly assist you.

This course comprises of 34 case studies that will enrich your learning experience. In addition, we also have 3 Projects that will enhance your implementation skills. Below are few case studies which are part of this course:

Case Study 1: Maple Leaves Ltd is a start-up company which makes herbs from different types of plants and its leaves. Currently the system they use to classify the trees which they import in a batch is quite manual. A laborer from his experience decides the leaf type and subtype of plant family. They have asked us to automate this process and remove any manual intervention from this process.

You have to classify the plant leaves by various classifiers from different metrics of the leaves and to choose the best classifier for future reference.

Case Study 2: BookRent is the largest online and offline book rental chain in India. Company charges a fixed fee per month plus rental per book. So, company makes more money when user rent more books.

You as an ML expert and must model recommendation engine so that user gets recommendation of books based on behavior of similar users. This will ensure that users are renting books based on their individual taste.

Company is still unprofitable and is looking to improve both revenue and profit. Compare the Error using two approaches – User Based Vs Item Based

Predict the survival of a horse based on various observed medical conditions. Load the data from ‘horses.csv’ and observe whether it contains missing values. Replace the missing values by the most frequent value in each column. Fit a decision tree classifier and observe the accuracy. Fit a random forest classifier and observe the accuracy.

Case Study 4: Principal component analysis using scikit learn.

Load the digits dataset from sklearn and write a helper function to plot the image. Fit a logistic regression model and observe the accuracy.

Using scikit learn perform a PCA transformation such that the transformed dataset can explain 95% of the variance in the original dataset. Compare it with a model and also comment on the accuracy. Compute the confusion matrix and count the number of instances that has gone wrong. For each of the wrong sample, plot the digit along with predicted and original label.

Case Study 5: Read the datafile “letterCG.data” and set all the numerical attributes as features. Split the data in to train and test sets.

Fit a sequence of AdaBoostClassifier with varying number of weak learners ranging from 1 to 16, keeping the max_depth as 1. Plot the accuracy on test set against the number of weak learners, using decision tree classifier as the base classifier.

Problem Statement: You as ML expert have to do analysis and modeling to predict the number of shares of an article given the input parameters.

Actions to be performed:

Load the corresponding dataset. Perform data wrangling, visualization of the data and detect the outliers, if any. Use the plotly library in Python to draw useful insights out of data. Perform regression modeling on the dataset as well as decision tree regressor to achieve your goal. Also, use scaling processes, PCA along with boosting techniques to optimize your model to the fullest.

Project #2:

Industry: FMCG

Problem Statement: You as an ML expert have to cluster the countries based on various sales data provided to you across years.

Actions to be performed:

You have to apply an unsupervised learning technique like K means or Hierarchical clustering so as to get the final solution. But before that, you have to bring the exports (in tons) of all countries down to the same scale across years. Plus, as this solution needs to be repeatable you will have to do PCA so as to get the principal components which explain the max variance.

Goal: In this module, you will learn about developing a smart learning algorithm such that the learning becomes more and more accurate as time passes by. You will be able to define an optimal solution for an agent based on agent environment interaction.

Goal: In this module, you will learn about Time Series Analysis to forecast dependent variables based on time. You will be taught different models for time series modelling such that you analyse a real time dependent data for forecasting.

Goal: In this module, you will learn about selecting one model over another. Also, you will learn about Boosting and its importance in Machine Learning. You will learn on how to convert weaker algorithms to stronger ones.

Goal: In this module, you will learn how to approach and implement a Project end to end, and a Subject Matter Expert will share his experience and insights from the industry to help you kickstart your career in this domain. Finally, we will be having a Q&A and doubt clearing session.

edureka is committed to provide you an awesome learning experience through world-class content and best-in-class instructors. We will create an ecosystem through this training, that will enable you to convert opportunities into job offers by presenting your skills at the time of an interview. We can assist you in resume building and also share important interview questions once you are done with the training. However, please understand that we are not into job placements.

We have limited number of participants in a live session to maintain the Quality Standards. So, unfortunately participation in a live class without enrollment is not possible. However, you can go through the sample class recording and it would give you a clear insight about how are the classes conducted, quality of instructors and the level of interaction in a class.

All the instructors at edureka are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by edureka for providing an awesome learning experience to the participants.

Viresh Dagade

BigData Evangelist and Trainer
I am thankful to Edureka which is one of the best Educational organization. I have undergone two highly rated courses (Big data and Hadoop, Spark and Scala). Now i am doing well with the stuff learnt, after getting certified for big data and hadoop, I'm getting many offers from many companies. After the great experience of learning hadoop technology, I am now keen to enroll for Data science course. I hope i get the same learning experience which i got while undergoing my previous courses. I heartily thank edureka for helping me to make my career. The overall team [Trainers, support team, online support team] is the best.Read More Read Less

Shilpa Chutake

Financial Analyst, JPMorgan Chase & Co.
I was taking a course for Data Visualization with Tableau , and had wonderful experience with edureka, The instructors are well presentable and dedicated and have gone extra mile to provide the insights for the course. The instructor had done a great job to explain each and every feature with a real life example and provided hands on live examples during the sessions. Very well done edureka, I am willing to take some courses from you in near future and thanks you for making my learning experience knowledgeable and enjoyable. Definitely worth the effort and good value for money.Read More Read Less

Mohit Sharma

I have been subscribing to Edureka's courses for almost a year now, primarily related to Big Data and Data analytics. These courses have helped me to gain that competitive edge which is required at the job. Also, their courses cover a breadth of topics and range from computer programming languages like Java to Data Visualisation. There is also constant updation done on these courses, and you can talk to their support staff at any time for any assistance. I found the faculties very knowledgeable, and all the courses that I enrolled in were delivered in a very detailed and professional manner. For any person looking for online training, I can recommend Edureka without hesitation.Read More Read Less

Anil Algole

Principle Consultant at Infosys
Experience with Edureka is world class. I took 2 courses Informatica PowerCenter 9.x and Tableau Certification Training. I feel both the courses had extremely knowledgeable instructors, professional course delivery, recorded classes, great customer support and the access to needed tools at the comfort of your time and place (home). I have not seen such a value for money for anywhere in the world. I will keep taking many many courses with Edureka! Thank you for your help I am able to increase my billing rate and subject level expertise."Read More Read Less

Tanmoy Kar

The online course delivered by Edureka on big data, Hadoop - developer is really nice. The first thing of Edureka is that, the very first day of your registration, you have access the full tutorial ( record of some previous batch) and which will provide enough knowledge/teaching, so whenever you are attending your actual training session, you are not a fresher of the session, but a kind, expert and you can clear any knowledge gap.More of that, as you are getting 2 lectures for the same session, your knowledge is much more, than you would have expected. As these recording will be available you for ever, you always go again and again and again.The help/administration/support is really really good.For Hadoop big Data developer, I will recommend to join.ThanksRead More Read Less